LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Benatar, Naisan; Aickelin, Uwe; Garibaldi, Jonathan M. (2013)
Languages: English
Types: Unknown
Subjects: Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing
Type-1 fuzzy logic has frequently been used in control systems. However this method is sometimes shown to be too restrictive and unable to adapt in the presence of uncertainty. In this paper we compare type-1 fuzzy control with several other fuzzy approaches under a range of uncertain conditions. Interval type-2 and non-stationary fuzzy controllers are compared, along with ‘dual surface’ type-2 control, named due to utilising both the lower and upper values produced from standard interval type-2 systems. We tune a type-1 controller, then derive the membership functions and footprints of uncertainty from the type-1 system and evaluate them using a simulated autonomous sailing problem with varying amounts of environmental uncertainty. We show that while these more sophisticated controllers can produce better performance than the type-1 controller, this is not guaranteed and that selection of Footprint of Uncertainty (FOU) size has a large effect on this relative performance.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] L. A. Zadeh, “The concept of a linguistic variable and its application to approximate reasoning i,” Information Sciences, pp. 199-249, 1975.
    • [2] D. Wu and W. W. Tan, “Interval type-2 fuzzy pi controllers: Why they are more robust,” in IEEE International Conference on Granular Computing, 2010.
    • [3] J. M. Mendel and R. I. John, “Footprint of uncertainty and its importance to type-2 fuzzy sets,” in Proceedings of 6th IASTED International Conference on Artificial Intelligence and Soft Computing (ASC 2002), Bannf, Canada, 17 - 19 July 2002, pp. 587-592.
    • [4] J. M. Mendel, R. I. John, and F. Liu, “Interval type-2 fuzzy logic systems made simple,” IEEE Transactions on Fuzzy Systems, vol. 14, 2006.
    • [5] N. N. Karnik, J. M. Mendel, and Q. Liang, “Type 2 fuzzy logic systems,” IEEE Transactions on Fuzzy Systems, vol. 7, 1999.
    • [6] H. Hagras, “A hierachical type 2 fuzzy logic control architechture for autonomous mobile robots,” IEEE Transactions on Fuzzy Systems, vol. 12, 2004.
    • [7] P. A. Birkin and J. M. Garibaldi, “A novel dual-surface type-2 controller for micro robots,” in Proceedings of FUZZ-IEEE, 2010.
    • [8] J. M. Garibaldi, M. Jaroszewski, and S. Musikasuwan, “Non-stationary fuzzy sets,” IEEE Transactions on Fuzzy Systems, vol. 16 (4), pp. 1072- 1086, 2008.
    • [9] J. M. Garibaldi, S. Musikasuwan, and T. Ozen, “The association between non-stationary and interval type-2 fuzzy sets: A case study,” in Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 05), Reno, USA, 2005, pp. 224-229.
    • [10] J. Abril, J. Salon, and O. Calvo, “Fuzzy control of a sailboat,” International Journal of Approximate Reasoning, vol. 16, pp. 359-375, 1997. [Online]. Available: http://mapp1.de.unifi.it/persone/Allotta/ICAD/Abril1997.pdf
    • [11] R. Stelzer, T. Pro¨ll, and R. I. John, “Fuzzy logic control system for autonomous sailboats,” in Proceedings IEEE International Fuzzy Systems Conference FUZZ-IEEE 2007, 2007, pp. 1-6.
    • [12] B. Yves, “Iboat: an autonomous robot for long-term offshore operation,” in Proceedings MELECON 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference, 2009.
    • [13] C. Sauze´ and M. Neal, “A neuro-endocrine inspired approach to long term energy autonomy in sailing robots,” in Proceedings of TAROS (Towards Autonomous Robotic Systems), Bannf, Canada, 17 - 19 July 2010, pp. 255-262.
    • [14] R. Stelzer, “Robotic sailing: Overview,” OGAI Journal (Oesterreichische Gesellschaft fuer Artificial Intelligence), vol. 27, no. 2, pp. 2-3, June 2008.
    • [15] R. Stelzer and T. Pro¨ll, “Autonomous sailboat navigation for short course racing,” Robotics and Autonomous Systems, vol. 56, no. 7, pp. 604-614, July 2008.
    • [16] C. Sauze´ and M. Neal, “Design considerations for sailing robots performing long term autonomous oceanography,” in Proceedings of The International Robotic Sailing Conference, 2008.
    • [17] C. Sauze´, “Control software for a sailing robot,” Master's thesis, University of Wales, Aberystwyth, 2005.
    • [18] D. Wu and J. Mendel, “On the continuity of type-1 and interval type-2 fuzzy logic systems,” IEEE Transactions on Fuzzy Systems, pp. 179-192, 2011.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article